Abstract

AbstractPolymer flooding has proved an effective technique to improve development efficiency in heterogeneous reservoirs. Previously, operators usually employed continuous injection of large polymer slugs. However, problems existed including premature injection profile reversal during development, ineffective circulation of polymer solution in low-permeability zones, and excessive polymer consumption in the late development stage. The paper proposed a combination method, named as polymer-alternating-water (PAW), to solve the issues of traditional polymer flooding. The characteristic of this method is injecting water slugs between polymer slugs during the polymer flooding process. At present, research on the PAW technique is limited, with the operational parameters, oil recovery mechanisms, and applicability under various reservoir conditions remaining unclear. In this work, a numerical polymer flooding model is developed using the commercial CMG-STARS reservoir simulation module to investigate the oil displacement performance of PAW. Numerical simulations are performed to determine the optimal parameters for maximizing oil recovery factor. The results indicated compared with continuous polymer flooding, PAW shows multiple peaks in daily oil production rate, with a significantly decreased decline rate, resulting in a 1.47% increase in recovery factor. Under different reservoir conditions including mean permeability, heterogeneity, and crude oil viscosity, PAW can achieve further improvements on the basis of continuous polymer flooding. Polymer adsorption and injection concentration significantly impact the recovery factor, requiring further optimization for field applications. In this study, better polymer flooding performance was achieved when the number of alternating cycles of PAW was 2, and the injected alternating water slug volume was 50%. This study contributes to a deeper understanding of the key mechanisms and parameters in PAW enhanced oil recovery process, thereby providing guidance for the further optimization and field application of this technique.

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